Falconer is an AI-powered enterprise knowledge brain focused on keeping engineering documentation accurate, searchable, and up to date in real time. By syncing GitHub, Slack, Linear, and other tech stack tools, it builds a unified knowledge base and provides verified information to every person and every AI agent.
Key Capabilities
Falconer is built around three core capabilities: knowledge health, answer retrieval, and knowledge capture.
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Knowledge health: automatically discovers outdated, missing, duplicate, and conflicting knowledge, alerting before information slows down team decisions or misleads AI agents. When products change, Falconer can locate outdated documentation and propose precise update suggestions.
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Answer retrieval: provides cited answers across documents, code, tasks, and conversations, so users can obtain reliable information without interrupting colleagues. Supports sharing context through Slack, MCP, and a fast web app.
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Knowledge capture: automatically turns code, Slack discussion threads, meetings, and agent sessions into structured documentation, with no manual writing required.
In addition, Falconer provides Spaces, giving each team a focused view while preserving the context, permissions, and decisions needed to connect everything, without migration.
How to Use
After users connect data sources, Falconer builds a knowledge base and shares context through Slack, MCP, and the web app. The platform is read-only by default and writes to connected systems only when explicitly enabled. Users can choose their preferred model and inference provider while keeping company knowledge portable across models and agents. Falconer cites the company knowledge behind every answer, ensuring everything is verifiable.
Enterprise-grade features include: fine-grained permission management, permissioned workspaces (gated protection for sensitive knowledge), cloud-hosted, managed single-tenant, and fully on-premises deployment options, as well as SOC 2 Type II and HIPAA compliance, encryption in transit and at rest, and no training on customer data.
Use Cases
Falconer is suitable for engineering, customer success, product, sales, and operations teams. Specific scenarios include: keeping engineers working without interruptions; unblocking customer success teams without escalating to engineering; fixing outdated runbooks, onboarding guides, and support documentation; giving every agent 100% up-to-date company knowledge; and halving employee onboarding time. New employees can instantly get trustworthy answers without frequently disturbing senior colleagues. AI agents can obtain real-time, cited product and company knowledge, avoiding hallucinations.
Limitations
Information regarding pricing, specific prices, free trial policies, etc., is not currently provided in the available materials. The specific support lists of model and inference providers, the detailed requirements of each deployment option, and the complete list of supported platform integrations are not explained in detail in the materials.
